Whisper Small He with punctuation- Tom Apt
This model is a fine-tuned version of openai/whisper-small on the Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.6067
- Wer Ortho: 44.9468
- Wer: 41.3437
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.0739 | 0.2242 | 50 | 0.9126 | 51.8174 | 48.0993 |
| 0.7849 | 0.4484 | 100 | 0.7600 | 49.1209 | 45.4251 |
| 0.6366 | 0.6726 | 150 | 0.6490 | 47.3700 | 43.7454 |
| 0.5582 | 0.8969 | 200 | 0.6033 | 46.5499 | 42.8098 |
| 0.3775 | 1.1211 | 250 | 0.6004 | 46.1584 | 42.2941 |
| 0.3617 | 1.3453 | 300 | 0.5918 | 46.5352 | 42.8687 |
| 0.3631 | 1.5695 | 350 | 0.5849 | 45.6339 | 41.7784 |
| 0.3332 | 1.7937 | 400 | 0.5885 | 44.9690 | 40.9754 |
| 0.3093 | 2.0179 | 450 | 0.5808 | 44.5109 | 40.8944 |
| 0.1865 | 2.2422 | 500 | 0.6067 | 44.9468 | 41.3437 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0